Study of an on-line measurement method for the salt parameters of soda-saline soils based on the texture features of cracks

Zhao

et al. 2019

Remote Sensing

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The spectral features of soils are a comprehensive representation of their physicochemical parameters, surface states, and internal structures. To date, spectral measurements have been mostly performed for powdered soils and smooth aggregate soils, but rarely for cracked soils; a common state of soda-saline soils. In this study, we measured the spectral features of 57 saline soil samples in powdered, aggregate, and cracked states for comparison. We then explored in depth the factors governing soil spectral features to build up simple and multiple linear regression models between the spectral features and physicochemical parameters (salt content, Na+, pH, and electronic conductivity (EC)) of saline soils in different states. We randomly selected 40 samples to construct the models, and used the remaining 17 samples for validation. Our results indicated that the regression models worked more effectively in predicting physicochemical parameters for cracked soils than for other soils. Subsequently, the crack ratio (CR) was introduced into the regression models to modify the spectra of soils in powdered and aggregate states. The accuracy of prediction was improved, evidenced by a 2–11% decrease in the parameters mean absolute error (MAE).

Section: Introductionmentioning

confidence: 99%

Correlation between Spectral Characteristics and Physicochemical Parameters of Soda-Saline Soils in Different States

Zhao

et al. 2019

Remote Sensing

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“…Finally, the open operation was then performed with a given threshold to reduce the small spot noise in every binary image ( Figure 3e). After the above processes, a distance of 40 pixels was selected as sampling interval in order to fully preserve the GLCM texture information and reduce the computational complexity, the mean CON texture features of all cracked soil samples were then computed based on the CON computed from GLCMs in 0 • , 45 • , 90 • , and 135 • directions [43].…”

Section: Texture Feature Extractionmentioning

confidence: 99%

Quantitative Analysis of Spectral Response to Soda Saline-AlkaliSoil after Cracking Process: A Laboratory Procedure to Improve Soil Property Estimation

et al. 2019

Remote Sensing

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Cracking on the surface of soda saline-alkali soil is very common. In most previous studies, spectral prediction models of soil salinity were less accurate since spectral measurements were usually performed on 2 mm soil samples which cannot represent true soil surface condition very well. The objective of our research is to provide a procedure to improve soil property estimation of soda saline-alkali soil based on spectral measurement considering the texture feature of the soil surface with cracks. To achieve this objective, a cracking test was performed with 57 soil samples from Songnen Plain of China, the contrast (CON) texture feature of crack images of soil samples was then extracted from grey level co-occurrence matrix (GLCM). The original reflectance was then measured and the mixed reflectance considering the CON texture feature was also calculated from both the block soil samples (soil blocks separated by crack regions) and the comparison soil samples (soil powders with 2 mm particle size). The results of analysis between spectra and the main soil properties indicate that surface cracks can reduce the overall reflectivity of the soda saline-alkali soil and thus increasing the spectral difference among the block soil samples with different salinity levels. The results also show that both univariate and multivariate linear regression models considering the CON texture feature can greatly improve the prediction accuracy of main soil properties of soda saline-alkali soils, such as Na+, EC and salinity, which also can reduce the intensity of field spectral measurements under natural condition.

“…After a series of studies on 32 saline-alkali soils, Smith et al [32] determined the relationship between the cation exchange capacity of the soils and their linear expansion coefficient (COLE), with a correlation coefficient up to 0.81. Ren et al [33,34] extracted the textural features of crack patterns, and quantitatively analyzed the relationship between texture feature and salinity of saline-sodic soils. Zhang et al [35] conducted desiccation tests of saline-sodic soils in the laboratory to analyze the effects of NaCl content on their cracking behavior during water evaporation.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of the Spectral Response to Soil Salinity of Saline-Sodic Soils under Different Surface Conditions

Zhao

et al. 2018

IJERPH

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Desiccation cracking is a very common surface soil phenomenon of saline-sodic land. The objective of this study was to investigate the effects of salt content on the spectral reflectance of soil with and without desiccation cracks. To achieve our objective, a cracking test was performed using 17 soil samples. Following the tests, crack parameters were extracted, and correlation analysis was then performed between crack parameters and four soil properties: Na+, salinity (total concentration of ions), pH, and electric conductivity (EC). In order to select the optimum spectral measurement method and develop prediction models, spectral response to different soil properties were compared between the cracked soil samples and the comparative soil samples composed of the 2 mm particle size fraction processed by traditional methods. The results indicate that soil salinity dominated cracking propagation with a positive correlation. Since area and volume scattering are closer to what occurs in the field, a greater spectral response to soil properties was found for cracked soil samples relative to the comparative soil samples in the near-infrared and shortwave-infrared regions. The R2 of optimal linear prediction models based on the cracked soil samples were 0.74, 0.67, 0.58, and 0.67 for Na+, salinity, pH, and EC, respectively.